APPLICATION OF RESPONSE SURFACE METHODOLOGY TO IMPROVE TRAFFIC SIGNAL PERFORMANCE AND MINIMIZE LANE INEFFICIENCY

Abstract

Maintaining saturation flow at signalized intersections is crucial for both intersection capacity and sustainable traffic management. Efficient signal systems reduce congestion, lower emissions, and improve urban air quality. Factors such as signal timing, traffic demand, vehicle types, and intersection design significantly impact traffic flow efficiency. This study investigates the signal system and traffic flow parameters affecting lane inefficiency using Response Surface Methodology (RSM). Key factors included green time (G), the ratio of unused green time to total green time (theta/G), and discharge flow rate (beta), while lane inefficiency (delta) served as the response variable. The full quadratic model was identified as the best model for explaining lane inefficiency due to its high adjusted R-squared value and low error values. The study recommends a green time of 30 seconds and a discharge flow rate of 0.540 vehicles per second per lane to obtain minimum lane inefficiency. These findings support decision-makers in creating smarter, more efficient signal-controlled intersections, ultimately contributing to sustainable urban transport infrastructure by improving traffic flow, reducing emissions, and lowering fuel consumption.